Graph neural networks (GNNs) are powerful machine learning models for various graph
learning tasks. Recently, the limitations of the expressive power of various GNN models …

As users interact via social media spaces, like Twitter, they form connections that emerge
into complex social network structures. These connections are indicators of content sharing …

The internet and the mobile phone have disrupted many of our conventional understandings
of ourselves and our relationships, raising anxieties and hopes about their effects on our …

Social media and Internet data offer rich opportunities and vexing challenges for
sociocultural research. Explaining and extending prior approaches, Netnography …

Analyzing Social Media Networks with NodeXL offers backgrounds in information studies,
computer science, and sociology. This book is divided into three parts: analyzing social …

Companies' Facebook pages have emerged as a commonly used marketing channel and
their importance as a sales channel is likely to increase. Details about consumers' …

Online discussion communities have become a widely used medium for interaction,
enabling conversations across a broad range of topics and contexts. Their success …

Billions of people participate in online social activities. Most users participate as readers of
discussion boards, searchers of blog posts, or viewers of photos. A fraction of users become …

Organizations increasingly initiate Internet-based innovation-contest communities through
which individuals can interact and contribute to the innovation process. To successfully …

We investigate how to organize a large collection of geotagged photos, working with a
dataset of about 35 million images collected from Flickr. Our approach combines content …